LogisticRegression

Logistic-regression family for associate$regression()

Description

LogisticRegression implements binomial generalized linear models for binary outcomes. It supports the same covariate, split.by, and interaction surface as LinearRegression, but reports estimates on the log-odds scale.

Summary rows follow the glm association schema. Returned artifacts are:

  • prediction.grid, a probability-scale effect grid for the tested predictor

Super class

PolyGenius::RegressionFamily -> LogisticRegression

Methods

Public methods

Inherited methods

Method new()

Register the canonical family key used by the engine.

Usage 
LogisticRegression$new()
Returns

The initialized family object with family.name = “glm”.

Method validate.frame()

Ensure the resolved outcome is binary before fitting.

Usage 
LogisticRegression$validate.frame(frame, cell, fit.specs, conf.level)
Arguments
frame

Cell-specific PolyGeniusFrame.

cell

Named fit-grid cell.

fit.specs

Additional family-specific fitting arguments.

conf.level

Confidence level for intervals.

Returns

Invisibly TRUE when validation succeeds.

Method prepare.frame()

Build the complete-case logistic-regression payload.

Usage 
LogisticRegression$prepare.frame(frame, cell, fit.specs, conf.level)
Arguments
frame

Cell-specific PolyGeniusFrame.

cell

Named fit-grid cell.

fit.specs

Additional family-specific fitting arguments.

conf.level

Confidence level for intervals.

Returns

A model-ready fit payload with the outcome coded as 0/1.

Method build.formula()

Build the logistic-regression formula for one fit payload.

Usage 
LogisticRegression$build.formula(frame)
Arguments
frame

Fit payload returned by prepare.frame().

Returns

A model formula object.

Method fit.model()

Fit the binomial generalized linear model for one cell.

Usage 
LogisticRegression$fit.model(formula, frame, ...)
Arguments
formula

Model formula returned by build.formula().

frame

Fit payload returned by prepare.frame().

…

Additional arguments passed to stats::glm().

Returns

A fitted stats::glm object.

Method build.summary.rows()

Convert the fitted logistic model to regression-schema rows.

Usage 
LogisticRegression$build.summary.rows(
  fit,
  fit.data,
  cell,
  fit.specs,
  conf.level,
  formula
)
Arguments
fit

Fitted stats::glm object.

fit.data

Fit payload returned by prepare.frame().

cell

Named fit-grid cell.

fit.specs

Additional family-specific fitting arguments.

conf.level

Confidence level for intervals.

formula

Display formula string.

Returns

A data frame following the concrete association schema.

Method build.artifacts()

Return probability-grid and profile artifacts.

Usage 
LogisticRegression$build.artifacts(
  fit,
  fit.data,
  cell,
  fit.specs,
  conf.level,
  formula
)
Arguments
fit

Fitted stats::glm object.

fit.data

Fit payload returned by prepare.frame().

cell

Named fit-grid cell.

fit.specs

Additional family-specific fitting arguments.

conf.level

Confidence level for intervals.

formula

Display formula string.

Returns

A named list with prediction.grid and profile.table.

Method clone()

The objects of this class are cloneable with this method.

Usage 
LogisticRegression$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.